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Showing papers on "Robust control published in 2011"


Journal ArticleDOI
TL;DR: Two new robust adaptive control algorithms are developed by introducing a well defined smooth function and using a Nussbaum function to compensate for the nonlinear term arising from the input saturation.
Abstract: In this technical note, we consider adaptive control of single input uncertain nonlinear systems in the presence of input saturation and unknown external disturbance. By using backstepping approaches, two new robust adaptive control algorithms are developed by introducing a well defined smooth function and using a Nussbaum function. The Nussbaum function is introduced to compensate for the nonlinear term arising from the input saturation. Unlike some existing control schemes for systems with input saturation, the developed controllers do not require assumptions on the uncertain parameters within a known compact set and a priori knowledge on the bound of the external disturbance. Besides showing global stability, transient performance is also established and can be adjusted by tuning certain design parameters.

879 citations


Journal ArticleDOI
TL;DR: A novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method and a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method.
Abstract: In this paper, a novel data-driven robust approximate optimal tracking control scheme is proposed for unknown general nonlinear systems by using the adaptive dynamic programming (ADP) method. In the design of the controller, only available input-output data is required instead of known system dynamics. A data-driven model is established by a recurrent neural network (NN) to reconstruct the unknown system dynamics using available input-output data. By adding a novel adjustable term related to the modeling error, the resultant modeling error is first guaranteed to converge to zero. Then, based on the obtained data-driven model, the ADP method is utilized to design the approximate optimal tracking controller, which consists of the steady-state controller and the optimal feedback controller. Further, a robustifying term is developed to compensate for the NN approximation errors introduced by implementing the ADP method. Based on Lyapunov approach, stability analysis of the closed-loop system is performed to show that the proposed controller guarantees the system state asymptotically tracking the desired trajectory. Additionally, the obtained control input is proven to be close to the optimal control input within a small bound. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed control scheme.

530 citations


Journal ArticleDOI
TL;DR: This paper analyzes the stability problem of the grid-connected voltage-source inverter (VSI) with LC filters, which demonstrates that the possible grid-impedance variations have a significant influence on the system stability when conventional proportional-integrator (PI) controller is used for grid current control.
Abstract: This paper analyzes the stability problem of the grid-connected voltage-source inverter (VSI) with LC filters, which demonstrates that the possible grid-impedance variations have a significant influence on the system stability when conventional proportional-integrator (PI) controller is used for grid current control. As the grid inductive impedance increases, the low-frequency gain and bandwidth of the PI controller have to be decreased to keep the system stable, thus degrading the tracking performance and disturbance rejection capability. To deal with this stability problem, an H∞ controller with explicit robustness in terms of grid-impedance variations is proposed to incorporate the desired tracking performance and the stability margin. By properly selecting the weighting functions, the synthesized H∞ controller exhibits high gains at the vicinity of the line frequency, similar to the traditional proportional-resonant controller; meanwhile, it has enough high-frequency attenuation to keep the control loop stable. An inner inverter-output-current loop with high bandwidth is also designed to get better disturbance rejection capability. The selection of weighting functions, inner inverter-output-current loop design, and system disturbance rejection capability are discussed in detail in this paper. Both simulation and experimental results of the proposed H∞ controller as well as the conventional PI controller are given and compared, which validates the performance of the proposed control scheme.

388 citations


Journal ArticleDOI
TL;DR: This work proposes a quaternion-based hybrid feedback scheme that solves the global attitude tracking problem in three scenarios: full state measurements, only measurements of attitude, and measurements of attitudes with angular velocity measurements corrupted by a constant bias.
Abstract: It is well known that controlling the attitude of a rigid body is subject to topological constraints. We illustrate, with examples, the problems that arise when using continuous and (memoryless) discontinuous quaternion-based state-feedback control laws for global attitude stabilization. We propose a quaternion-based hybrid feedback scheme that solves the global attitude tracking problem in three scenarios: full state measurements, only measurements of attitude, and measurements of attitude with angular velocity measurements corrupted by a constant bias. In each case, the hybrid feedback is dynamic and incorporates hysteresis-based switching using a single binary logic variable for each quaternion error state. When only attitude measurements are available or the angular rate is corrupted by a constant bias, the proposed controller is observer-based and incorporates an additional quaternion filter and bias observer. The hysteresis mechanism enables the proposed scheme to simultaneously avoid the “unwinding phenomenon” and sensitivity to arbitrarily small measurement noise that is present in discontinuous feedbacks. These properties are shown using a general framework for hybrid systems, and the results are demonstrated by simulation.

363 citations


Journal ArticleDOI
TL;DR: In this article, a tube-based model predictive control of linear systems is proposed to achieve robust control of nonlinear systems subject to additive disturbances, where the local linear controller is replaced by an ancillary model predictive controller that forces the trajectories of the disturbed system to lie in a tube whose center is the reference trajectory.
Abstract: This paper extends tube-based model predictive control of linear systems to achieve robust control of nonlinear systems subject to additive disturbances. A central or reference trajectory is determined by solving a nominal optimal control problem. The local linear controller, employed in tube-based robust control of linear systems, is replaced by an ancillary model predictive controller that forces the trajectories of the disturbed system to lie in a tube whose center is the reference trajectory thereby enabling robust control of uncertain nonlinear systems to be achieved. Copyright © 2011 John Wiley & Sons, Ltd.

344 citations


Journal ArticleDOI
TL;DR: Sufficient conditions are given for the stability of linear switched systems with dwell time and with polytopic type parameter uncertainty and a Lyapunov function, in quadratic form, which is non-increasing at the switching instants is assigned to each subsystem.
Abstract: Sufficient conditions are given for the stability of linear switched systems with dwell time and with polytopic type parameter uncertainty. A Lyapunov function, in quadratic form, which is non-increasing at the switching instants is assigned to each subsystem. During the dwell time, this function varies piecewise linearly in time after switching occurs. It becomes time invariant afterwards. This function leads to asymptotic stability conditions for the nominal set of subsystems that can be readily extended to the case where these subsystems suffer from polytopic type parameter uncertainties. The method proposed is then applied to stabilization via state-feedback both for the nominal and the uncertain cases.

333 citations


Journal ArticleDOI
TL;DR: The problem of robust mode-dependent delayed state feedback H∞ control is investigated for a class of uncertain time-delay systems with Markovian switching parameters and mixed discrete, neutral, and distributed delays using Lyapunov-Krasovskii functional theory.
Abstract: The problem of robust mode-dependent delayed state feedback H∞ control is investigated for a class of uncertain time-delay systems with Markovian switching parameters and mixed discrete, neutral, and distributed delays. Based on the Lyapunov-Krasovskii functional theory, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities for the stochastic stability and stabilization of the considered system using some free matrices. The desired control is derived based on a convex optimization method such that the resulting closed-loop system is stochastically stable and satisfies a prescribed level of H∞ performance, simultaneously. Finally, two numerical examples are given to illustrate the effectiveness of our approach.

324 citations


Journal ArticleDOI
TL;DR: This paper is concerned with the two-mode-dependent robust control synthesis of networked control systems where random delays existing in both forward controller-to-actuator (C-A) and feedback sensor- to-controller (S-C) communication links are modeled as Markov chains.

316 citations


Journal ArticleDOI
TL;DR: In this article, a non-linear disturbance observer-based robust control method is proposed to attenuate the mismatched disturbances and the influence of parameter variations from system output channels in a missile system with nonlinear dynamics in the presence of various uncertainties and external disturbances.
Abstract: Robust control of non-linear systems with disturbances and uncertainties is addressed in this study using disturbance observer-based control (DOBC) technique. In this framework, the `disturbance` is a generalised concept, which may include external disturbances, unmodelled dynamics and system parameter perturbations. The existing DOBC methods were only applicable for the case where disturbances and uncertainties satisfy so-called matching condition, that is, they enter the system in the same channel as the control inputs. By appropriately designing a disturbance compensation gain vector in the composite control law, a non-linear disturbance observer-based robust control method is proposed in this study to attenuate the mismatched disturbances and the influence of parameter variations from system output channels. The proposed method is applied to a missile system with non-linear dynamics in the presence of various uncertainties and external disturbances. Simulation shows that, compared with the widely used non-linear dynamic inversion control (NDIC) and NDIC plus integral action methods, the proposed method provides much better disturbance attenuation ability and stronger robustness against various parameter variations.

314 citations


Journal ArticleDOI
01 Dec 2011
TL;DR: Under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced significantly, and semiglobal uniform ultimate boundedness of all of the signals in the closed-loop system is guaranteed.
Abstract: This paper is concerned with robust stabilization problem for a class of nonaffine pure-feedback systems with unknown time-delay functions and perturbed uncertainties. Novel continuous packaged functions are introduced in advance to remove unknown nonlinear terms deduced from perturbed uncertainties and unknown time-delay functions, which avoids the functions with control law to be approximated by radial basis function (RBF) neural networks. This technique combining implicit function and mean value theorems overcomes the difficulty in controlling the nonaffine pure-feedback systems. Dynamic surface control (DSC) is used to avoid “the explosion of complexity” in the backstepping design. Design difficulties from unknown time-delay functions are overcome using the function separation technique, the Lyapunov-Krasovskii functionals, and the desirable property of hyperbolic tangent functions. RBF neural networks are employed to approximate desired virtual controls and desired practical control. Under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced significantly, and semiglobal uniform ultimate boundedness of all of the signals in the closed-loop system is guaranteed. Simulation studies are given to demonstrate the effectiveness of the proposed design scheme.

294 citations


Journal ArticleDOI
TL;DR: A multiple model/control-based SMC technique is proposed to reduce the level of parametric uncertainty to reduce observer-controller gains and is evaluated on a 2-DOF robot manipulator to demonstrate the effectiveness of the theoretical development.
Abstract: In the face of large-scale parametric uncertainties, the single-model (SM)-based sliding mode control (SMC) approach demands high gains for the observer, controller, and adaptation to achieve satisfactory tracking performance. The main practical problem of having high-gain-based design is that it amplifies the input and output disturbance as well as excites hidden unmodeled dynamics, causing poor tracking performance. In this paper, a multiple model/control-based SMC technique is proposed to reduce the level of parametric uncertainty to reduce observer-controller gains. To this end, we split uniformly the compact set of unknown parameters into a finite number of smaller compact subsets. Then, we design a candidate SMC corresponding to each of these smaller subsets. The derivative of the Lyapunov function candidate is used as a resetting criterion to identify a candidate model that approximates closely the plant at each instant of time. The key idea is to allow the parameter estimate of conventional adaptive sliding mode control design to be reset into a model that best estimates the plant among a finite set of candidate models. The proposed method is evaluated on a 2-DOF robot manipulator to demonstrate the effectiveness of the theoretical development.

Journal ArticleDOI
TL;DR: In this paper, the problem of robust static output feedback (SOF) control for networked control systems (NCSs) subject to network-induced delays and missing data is investigated and an approach based on the linear matrix inequality technique is proposed to efficiently solve a nonconvex BMI.
Abstract: In this paper, we investigate the problem of robust static output feedback (SOF) control for networked control systems (NCSs) subject to network-induced delays and missing data. The uncertain system matrices are assumed to lie in a convex polytope. The network-induced delays are time varying but within a given interval. The random data missing is characterized by the Bernoulli random binary distribution. Delay-dependent conditions for the exponential mean-square stability are first established in terms of matrix inequalities. Then, for the robust stabilization problem, the design of an SOF controller is presented by solving bilinear matrix inequalities (BMIs). In order to efficiently solve a nonconvex BMI, we propose an approach based on the linear matrix inequality technique. Furthermore, the developed approach is employed to design the remote proportional-integral-derivative (PID) controller for NCSs. The design of a digital PID controller is formulated as a synthesis problem of the SOF control via an augmentation method. Simulation examples illustrate the effectiveness of the proposed methods.

Journal ArticleDOI
TL;DR: The design of a prototype helicopter suitable for testing the direct approximate-adaptive control method is described, and the new method stops weight drift during a shake test and adapts on-line to a significant added payload, whereas e-modification cannot do both.

Journal ArticleDOI
TL;DR: This study presents a robust nonsingular terminal sliding-mode control (RNTSMC) system to achieve finite time tracking control (FTTC) for the rotor position in the axial direction of a nonlinear thrust active magnetic bearing (TAMB) system.
Abstract: This study presents a robust nonsingular terminal sliding-mode control (RNTSMC) system to achieve finite time tracking control (FTTC) for the rotor position in the axial direction of a nonlinear thrust active magnetic bearing (TAMB) system. Compared with conventional sliding-mode control (SMC) with linear sliding surface, terminal sliding-mode control (TSMC) with nonlinear terminal sliding surface provides faster, finite time convergence, and higher control precision. In this study, first, the operating principles and dynamic model of the TAMB system using a linearized electromagnetic force model are introduced. Then, the TSMC system is designed for the TAMB to achieve FTTC. Moreover, in order to overcome the singularity problem of the TSMC, a nonsingular terminal sliding-mode control (NTSMC) system is proposed. Furthermore, since the control characteristics of the TAMB are highly nonlinear and time-varying, the RNTSMC system with a recurrent Hermite neural network (RHNN) uncertainty estimator is proposed to improve the control performance and increase the robustness of the TAMB control system. Using the proposed RNTSMC system, the bound of the lumped uncertainty of the TAMB is not required to be known in advance. Finally, some experimental results for the tracking of various reference trajectories demonstrate the validity of the proposed RNTSMC for practical TAMB applications.

Journal ArticleDOI
TL;DR: The effectiveness of the proposed TSMC scheme is verified by numerical simulations and realistic experimentations, and the advantages of good transient response and robustness to uncertainties are indicated in comparison with a conventional proportional-integral control system and a CSMC scheme.
Abstract: In this paper, a total sliding-mode control (TSMC) scheme is designed for the voltage tracking control of a conventional dc-dc boost converter. This control strategy is derived in the sense of Lyapunov stability theorem such that the stable tracking performance can be ensured under the occurrence of system uncertainties. The salient feature of this control scheme is that the controlled system has a total sliding motion without a reaching phase as in conventional sliding-mode control (CSMC). Moreover, the effectiveness of the proposed TSMC scheme is verified by numerical simulations and realistic experimentations, and the advantages of good transient response and robustness to uncertainties are indicated in comparison with a conventional proportional-integral control system and a CSMC scheme.

Journal ArticleDOI
TL;DR: Two different approaches to robust output-feedback controller design are developed for the underlying T-S fuzzy affine systems with unreliable communication links in the form of linear matrix inequalities (LMIs).
Abstract: This paper investigates the problem of robust output-feedback control for a class of networked nonlinear systems with multiple packet dropouts. The nonlinear plant is represented by Takagi-Sugeno (T-S) fuzzy affine dynamic models with norm-bounded uncertainties, and stochastic variables that satisfy the Bernoulli random binary distribution are adopted to characterize the data-missing phenomenon. The objective is to design an admissible output-feedback controller that guarantees the stochastic stability of the resulting closed-loop system with a prescribed disturbance attenuation level. It is assumed that the plant premise variables, which are often the state variables or their functions, are not measurable so that the controller implementation with state-space partition may not be synchronous with the state trajectories of the plant. Based on a piecewise quadratic Lyapunov function combined with an S-procedure and some matrix inequality convexifying techniques, two different approaches to robust output-feedback controller design are developed for the underlying T-S fuzzy affine systems with unreliable communication links. The solutions to the problem are formulated in the form of linear matrix inequalities (LMIs). Finally, simulation examples are provided to illustrate the effectiveness of the proposed approaches.

Journal ArticleDOI
TL;DR: A new comparison model is proposed by employing a new approximation for delayed state, and then lifting method and simple Lyapunov-Krasovskii functional method are used to analyze the scaled small gain of this comparison model.
Abstract: This technical note focuses on analyzing a new model transformation of uncertain linear discrete-time systems with time-varying delay and applying it to robust stability analysis. The uncertainty is assumed to be norm-bounded and the delay intervally time-varying. A new comparison model is proposed by employing a new approximation for delayed state, and then lifting method and simple Lyapunov-Krasovskii functional method are used to analyze the scaled small gain of this comparison model. This new approximation results in a much smaller error than the existing ones. Based on the scaled small gain theorem, new stability criteria are proposed in terms of linear matrix inequalities. Moreover, it is shown that the obtained conditions can be established through direct Lyapunov method. Two numerical examples are presented to illustrate the effectiveness and superiority of our results over the existing ones.

Journal ArticleDOI
Amit Mohanty1, Bin Yao1
TL;DR: This paper considers the trajectory tracking of a robotic manipulator driven by electro-hydraulic actuators based on the indirect adaptive robust control (IARC) framework with necessary design modifications required to accommodate uncertain and nonsmooth nonlinearities of the hydraulic system.
Abstract: In a general direct adaptive robust control (DARC) framework, the emphasis is always on the guaranteed transient performance and accurate trajectory tracking in presence of uncertain nonlinearities and parametric uncertainties. Such a direct algorithm suffers from lack of modularity, controller-estimator inseparability, and poor convergence of parameter estimates. In the DARC design the parameters are estimated by gradient law with the sole purpose of reducing tracking error, which is typical of a Lyapunov-type design. However, when the controller-estimator module is expected to assist in secondary purposes such as health monitoring and fault detection, the requirement of having accurate online parameter estimates is as important as the need for the smaller tracking error. In this paper, we consider the trajectory tracking of a robotic manipulator driven by electro-hydraulic actuators. The controller is constructed based on the indirect adaptive robust control (IARC) framework with necessary design modifications required to accommodate uncertain and nonsmooth nonlinearities of the hydraulic system. The online parameter estimates are obtained through a parameter adaptation algorithm that is based on physical plant dynamics rather than the tracking error dynamics. While the new controller preserves the nice properties of the DARC design such as prescribed output tracking transient performance and final tracking accuracy, more accurate parameter estimates are obtained for prognosis and diagnosis purpose. Comparative experimental results are presented to show the effectiveness of the proposed algorithm.

Proceedings ArticleDOI
01 Dec 2011
TL;DR: A hybrid theoretical framework for robust and resilient control design in which the stochastic switching between structure states models unanticipated events and deterministic uncertainties in each structure represent the known range of disturbances is proposed.
Abstract: The tradeoff between robustness and resilience is a pivotal design issue for modern industrial control systems. The trend of integrating information technologies into control system infrastructure has made resilience an important dimension of the critical infrastructure protection mission. It is desirable that systems support state awareness of threats and anomalies, and maintain acceptable levels of operation or service in the face of unanticipated or unprecedented incidents. In this paper, we propose a hybrid theoretical framework for robust and resilient control design in which the stochastic switching between structure states models unanticipated events and deterministic uncertainties in each structure represent the known range of disturbances. We propose a set of coupled optimality criteria for a holistic robust and resilient design for cyber-physical systems. We apply this method to a voltage regulator design problem for a synchronous machine with infinite bus and illustrate the solution methodology with numerical examples.

Journal ArticleDOI
TL;DR: In this paper, an active fault-tolerant controller (AFTC) and a passive fault tolerant controller (PFTC) are designed for a 4.8 MW, variable speed, variable pitch wind turbine model with a fault in the pitch system.

Journal ArticleDOI
TL;DR: Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation.
Abstract: Robust control of a class of uncertain systems that have disturbances and uncertainties not satisfying “matching” condition is investigated in this paper via a disturbance observer based control (DOBC) approach. In the context of this paper, “matched” disturbances/uncertainties stand for the disturbances/uncertainties entering the system through the same channels as control inputs. By properly designing a disturbance compensation gain, a novel composite controller is proposed to counteract the “mismatched” lumped disturbances from the output channels. The proposed method significantly extends the applicability of the DOBC methods. Rigorous stability analysis of the closed-loop system with the proposed method is established under mild assumptions. The proposed method is applied to a nonlinear MAGnetic LEViation (MAGLEV) suspension system. Simulation shows that compared to the widely used integral control method, the proposed method provides significantly improved disturbance rejection and robustness against load variation.

Journal ArticleDOI
TL;DR: The proposed control scheme is of low complexity, utilizes partial state feedback and requires reduced levels of a priori system knowledge, and can be easily extended to systems affected by bounded state measurement errors, as well as to MIMO nonlinear systems in block triangular form.
Abstract: A universal controller is designed for cascade systems, involving dynamic uncertainty, unknown nonlinearities, exogenous disturbances and/or time-varying parameters, capable of guaranteeing prescribed performance for the output tracking error, as well as uniformly bounded signals in the closed loop. By prescribed performance we mean that the output tracking error should converge to a predefined arbitrarily small residual set, with convergence rate no less than a certain prespecified value, exhibiting maximum overshoot less than a sufficiently small preassigned constant. The proposed control scheme is of low complexity, utilizes partial state feedback and requires reduced levels of a priori system knowledge. The results can be easily extended to systems affected by bounded state measurement errors, as well as to MIMO nonlinear systems in block triangular form. Simulations clarify and verify the approach.

Journal ArticleDOI
TL;DR: The paper addresses a problem of design of distributed robust filters using the recent vector dissipativity theory and proposes a gradient descent type algorithm which allows the nodes to compute their estimator parameters in a decentralized manner.

Journal ArticleDOI
TL;DR: It is demonstrated that a neural network can be trained to provide the coefficients of a Finite Impulse Response (FIR) type approximator, that approximates to the response of a given analog PIλDμ controller having time varying action coefficients and differintegration orders.
Abstract: The applications of Unmanned Aerial Vehicles (UAVs) require robust control schemes that can alleviate disturbances such as model mismatch, wind disturbances, measurement noise, and the effects of changing electrical variables, e.g., the loss in the battery voltage. Proportional Integral and Derivative (PID) type controller with noninteger order derivative and integration is proposed as a remedy. This paper demonstrates that a neural network can be trained to provide the coefficients of a Finite Impulse Response (FIR) type approximator, that approximates to the response of a given analog PIλDμ controller having time varying action coefficients and differintegration orders. The results obtained show that the neural network aided FIR type controller is very successful in driving the vehicle to prescribed trajectories accurately. The response of the proposed scheme is highly similar to the response of the target PIλDμ controller and the computational burden of the proposed scheme is very low.

Journal ArticleDOI
TL;DR: It is demonstrated that a very fast dynamic behavior can be obtained with the proposed controller, which improves the transient response of the grid-connected DFIG, particularly under conditions of unbalanced voltage dips resulting from asymmetrical network faults.
Abstract: This paper proposes a new robust controller in a stationary reference frame for doubly fed induction generators (DFIGs) of grid-connected wind turbines. Initially, a DFIG dynamic model is derived from the voltage and flux equations in αβ coordinates, where uncertainties and disturbances intrinsic to the system are accounted for as perturbation terms are added to the nominal model. Then, a controller design procedure that guarantees the DFIG stability under uncertainties and disturbances at the grid side is presented in detail. It is demonstrated that a very fast dynamic behavior can be obtained with the proposed controller, which improves the transient response of the grid-connected DFIG, particularly under conditions of unbalanced voltage dips resulting from asymmetrical network faults. In order to conform with the fault ride-through capability requirements, this paper proposes a new reference strategy, which is divided into normal and fault operation modes. Experimental results are given to support the theoretical analysis and to illustrate the performance of the grid-connected DFIG with the proposed controller.

Journal ArticleDOI
TL;DR: In this article, the authors established a hierarchical platoon controller design framework comprising a feedback linearisation controller at the first layer and a guaranteed cost H� ₷-consuming controller, the kernel controller, at the second layer.
Abstract: The problem of autonomous platoon control via wireless communication network is studied in this study. Firstly, a novel hybrid model is established for the platoon's longitudinal movement, where disturbances of lead vehicle acceleration and wind gust, parameter uncertainties and intermediate uncertainties induced by communication network (e.g. time delay, quantisation and packet dropout) are given full considerations and involved in the model for the first time. Then, the authors establish a hierarchical platoon controller design framework comprising a feedback linearisation controller at the first layer and a guaranteed cost H ∞ controller at the second layer. By reducing the non-linear system to a linear model using the top layer feedback linearisation controller, a robust H ∞ controller, the kernel controller, is designed utilising novel techniques in robust control of time-delay systems. For the general objective of disturbance attenuation, string stability and robust platoon control to be achieved simultaneously, the robust H ∞ controller is complemented by additional conditions established for guaranteeing string stability and zero steady-state spacing errors. Simulations are given to show the efficiency of the proposed results.

Journal ArticleDOI
TL;DR: In this paper, the authors provide a broad perspective on this area of research known as ''probabilistic robust control'' and to address in a systematic manner recent advances, focusing on design methods based on the interplay between uncertainty randomization and convex optimization, and on the illustration of specific control applications.

Journal ArticleDOI
TL;DR: This paper proposes a control strategy for nonlinear constrained continuous-time uncertain systems which combines robust model predictive control (MPC) with sliding mode control (SMC) and some general regional input-to-state practical stability results for continuous- time systems are proved.
Abstract: This paper proposes a control strategy for nonlinear constrained continuous-time uncertain systems which combines robust model predictive control (MPC) with sliding mode control (SMC) In particular, the so-called Integral SMC approach is used to produce a control action aimed to reduce the difference between the nominal predicted dynamics of the closed-loop system and the actual one In this way, the MPC strategy can be designed on a system with a reduced uncertainty In order to prove the stability of the overall control scheme, some general regional input-to-state practical stability results for continuous-time systems are proved

Journal ArticleDOI
TL;DR: This paper presents an adaptive robust predictive current control for grid-connected three-phase inverters that exhibit zero steady-state current error by means of an adaptive strategy that works in parallel with the deadbeat algorithm, therefore preserving the typical fast response of the predictive law.
Abstract: This paper presents an adaptive robust predictive current control (RPCC) for grid-connected three-phase inverters that exhibit zero steady-state current error. The error correction is achieved by means of an adaptive strategy that works in parallel with the deadbeat algorithm, therefore preserving the typical fast response of the predictive law. The resulting control adapts to any particular L or LCL filter by estimation of the resistive part of the filter. As a variety of the RPCC class of control, it offers the best tradeoff between robustness and speed.

Journal ArticleDOI
TL;DR: In this article, the two-degree-of-freedom nature of UDE-based controllers is revealed, and the error dynamics of the system is determined by two filters, of which one determines the set-point tracking response and robustness, whereas the other determines the error feedback gain and the filter introduced to estimate the uncertainty and disturbances.
Abstract: The control algorithm based on the uncertainty and disturbance estimator (UDE) is a robust control strategy and has received wide attention in recent years. In this paper, the two-degree-of-freedom nature of UDE-based controllers is revealed. The set-point tracking response is determined by the reference model, whereas the disturbance response and robustness are determined by the error feedback gain and the filter introduced to estimate the uncertainty and disturbances. It is also revealed that the error dynamics of the system is determined by two filters, of which one is determined by the error feedback gain and the other is determined by the filter introduced to estimate the uncertainty and disturbances. The design of these two filters are decoupled in the frequency domain. Moreover, after introducing the UDE-based control, the Laplace transform can be applied to some time-varying systems for analysis and design because all the time-varying parts are lumped into a signal. It has been shown that, in addition to the known advantages over the time-delay control, the UDE-based control also brings better performance than the time-delay control under the same conditions. Design examples and simulation results are given to demonstrate the findings. Copyright © 2010 John Wiley & Sons, Ltd.